{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:4VCF7PAZ7SJGGEYAUCHD2RRLWX","short_pith_number":"pith:4VCF7PAZ","canonical_record":{"source":{"id":"2505.18149","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2025-05-23T17:57:43Z","cross_cats_sorted":[],"title_canon_sha256":"d0cb8f0cb2d5cc1df8e7c1565fcecea231d96fd1e0c9850d869896659a92145e","abstract_canon_sha256":"8208b539f05fde81f4bb319407d85b80d7f1ff873f2cada79e78c9e7d8a5dbb8"},"schema_version":"1.0"},"canonical_sha256":"e5445fbc19fc92631300a08e3d462bb5ebf7f554ac39bb0c3c887a427eeddfe1","source":{"kind":"arxiv","id":"2505.18149","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2505.18149","created_at":"2026-07-05T11:08:37Z"},{"alias_kind":"arxiv_version","alias_value":"2505.18149v1","created_at":"2026-07-05T11:08:37Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2505.18149","created_at":"2026-07-05T11:08:37Z"},{"alias_kind":"pith_short_12","alias_value":"4VCF7PAZ7SJG","created_at":"2026-07-05T11:08:37Z"},{"alias_kind":"pith_short_16","alias_value":"4VCF7PAZ7SJGGEYA","created_at":"2026-07-05T11:08:37Z"},{"alias_kind":"pith_short_8","alias_value":"4VCF7PAZ","created_at":"2026-07-05T11:08:37Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:4VCF7PAZ7SJGGEYAUCHD2RRLWX","target":"record","payload":{"canonical_record":{"source":{"id":"2505.18149","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2025-05-23T17:57:43Z","cross_cats_sorted":[],"title_canon_sha256":"d0cb8f0cb2d5cc1df8e7c1565fcecea231d96fd1e0c9850d869896659a92145e","abstract_canon_sha256":"8208b539f05fde81f4bb319407d85b80d7f1ff873f2cada79e78c9e7d8a5dbb8"},"schema_version":"1.0"},"canonical_sha256":"e5445fbc19fc92631300a08e3d462bb5ebf7f554ac39bb0c3c887a427eeddfe1","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:08:37.146220Z","signature_b64":"QkYDRCH5UO7gr3EskBuR+LZPeDdlhmkUbSjCLzwIxcXrGKjGNoMW1fejJbz9VakQdOW1HsbG8dpocaGLAZdKBg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"e5445fbc19fc92631300a08e3d462bb5ebf7f554ac39bb0c3c887a427eeddfe1","last_reissued_at":"2026-07-05T11:08:37.145733Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:08:37.145733Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2505.18149","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T11:08:37Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"TxR5kdu5RP1zKy1lKYiUYVcYm9+TshUrI1Ia1OkPiXld3Q8riHJG1w5CojQuouVSgNu3AVD8drvrBdxhwITqBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-07T18:36:36.424002Z"},"content_sha256":"228c3181d7c7684ad9cfba5255d25c490da9b4a72f88bbe9cc212a4af83531f7","schema_version":"1.0","event_id":"sha256:228c3181d7c7684ad9cfba5255d25c490da9b4a72f88bbe9cc212a4af83531f7"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:4VCF7PAZ7SJGGEYAUCHD2RRLWX","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"First Finish Search: Efficient Test-Time Scaling in Large Language Models","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Aradhye Agarwal, Ayan Sengupta, Tanmoy Chakraborty","submitted_at":"2025-05-23T17:57:43Z","abstract_excerpt":"Test-time scaling (TTS), which involves dynamic allocation of compute during inference, offers a promising way to improve reasoning in large language models. While existing TTS methods work well, they often rely on long decoding paths or require a large number of samples to be generated, increasing the token usage and inference latency. We observe the surprising fact that for reasoning tasks, shorter traces are much more likely to be correct than longer ones. Motivated by this, we introduce First Finish Search (FFS), a training-free parallel decoding strategy that launches $n$ independent samp"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2505.18149","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2505.18149/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T11:08:37Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"8wQyxTg6JAdWBw11FssUnxGRkF0wke2hk1t4spRsoYnNGJstLqjfk64oVOmeu6u8nGO89hh16oSs4Pwv1e0aAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-07T18:36:36.424589Z"},"content_sha256":"66bf48f165f47167b8d6a7dab7078581b1df1fa15cf5d19a89e113a95e68dfeb","schema_version":"1.0","event_id":"sha256:66bf48f165f47167b8d6a7dab7078581b1df1fa15cf5d19a89e113a95e68dfeb"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/4VCF7PAZ7SJGGEYAUCHD2RRLWX/bundle.json","state_url":"https://pith.science/pith/4VCF7PAZ7SJGGEYAUCHD2RRLWX/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/4VCF7PAZ7SJGGEYAUCHD2RRLWX/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-08-07T18:36:36Z","links":{"resolver":"https://pith.science/pith/4VCF7PAZ7SJGGEYAUCHD2RRLWX","bundle":"https://pith.science/pith/4VCF7PAZ7SJGGEYAUCHD2RRLWX/bundle.json","state":"https://pith.science/pith/4VCF7PAZ7SJGGEYAUCHD2RRLWX/state.json","well_known_bundle":"https://pith.science/.well-known/pith/4VCF7PAZ7SJGGEYAUCHD2RRLWX/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:4VCF7PAZ7SJGGEYAUCHD2RRLWX","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"8208b539f05fde81f4bb319407d85b80d7f1ff873f2cada79e78c9e7d8a5dbb8","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2025-05-23T17:57:43Z","title_canon_sha256":"d0cb8f0cb2d5cc1df8e7c1565fcecea231d96fd1e0c9850d869896659a92145e"},"schema_version":"1.0","source":{"id":"2505.18149","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2505.18149","created_at":"2026-07-05T11:08:37Z"},{"alias_kind":"arxiv_version","alias_value":"2505.18149v1","created_at":"2026-07-05T11:08:37Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2505.18149","created_at":"2026-07-05T11:08:37Z"},{"alias_kind":"pith_short_12","alias_value":"4VCF7PAZ7SJG","created_at":"2026-07-05T11:08:37Z"},{"alias_kind":"pith_short_16","alias_value":"4VCF7PAZ7SJGGEYA","created_at":"2026-07-05T11:08:37Z"},{"alias_kind":"pith_short_8","alias_value":"4VCF7PAZ","created_at":"2026-07-05T11:08:37Z"}],"graph_snapshots":[{"event_id":"sha256:66bf48f165f47167b8d6a7dab7078581b1df1fa15cf5d19a89e113a95e68dfeb","target":"graph","created_at":"2026-07-05T11:08:37Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2505.18149/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Test-time scaling (TTS), which involves dynamic allocation of compute during inference, offers a promising way to improve reasoning in large language models. While existing TTS methods work well, they often rely on long decoding paths or require a large number of samples to be generated, increasing the token usage and inference latency. We observe the surprising fact that for reasoning tasks, shorter traces are much more likely to be correct than longer ones. Motivated by this, we introduce First Finish Search (FFS), a training-free parallel decoding strategy that launches $n$ independent samp","authors_text":"Aradhye Agarwal, Ayan Sengupta, Tanmoy Chakraborty","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2025-05-23T17:57:43Z","title":"First Finish Search: Efficient Test-Time Scaling in Large Language Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2505.18149","kind":"arxiv","version":1},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:228c3181d7c7684ad9cfba5255d25c490da9b4a72f88bbe9cc212a4af83531f7","target":"record","created_at":"2026-07-05T11:08:37Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"8208b539f05fde81f4bb319407d85b80d7f1ff873f2cada79e78c9e7d8a5dbb8","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2025-05-23T17:57:43Z","title_canon_sha256":"d0cb8f0cb2d5cc1df8e7c1565fcecea231d96fd1e0c9850d869896659a92145e"},"schema_version":"1.0","source":{"id":"2505.18149","kind":"arxiv","version":1}},"canonical_sha256":"e5445fbc19fc92631300a08e3d462bb5ebf7f554ac39bb0c3c887a427eeddfe1","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"e5445fbc19fc92631300a08e3d462bb5ebf7f554ac39bb0c3c887a427eeddfe1","first_computed_at":"2026-07-05T11:08:37.145733Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:08:37.145733Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"QkYDRCH5UO7gr3EskBuR+LZPeDdlhmkUbSjCLzwIxcXrGKjGNoMW1fejJbz9VakQdOW1HsbG8dpocaGLAZdKBg==","signature_status":"signed_v1","signed_at":"2026-07-05T11:08:37.146220Z","signed_message":"canonical_sha256_bytes"},"source_id":"2505.18149","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:228c3181d7c7684ad9cfba5255d25c490da9b4a72f88bbe9cc212a4af83531f7","sha256:66bf48f165f47167b8d6a7dab7078581b1df1fa15cf5d19a89e113a95e68dfeb"],"state_sha256":"c0d5f01385c70faf6e89ab9d4577f6e8ed2f5bcf58b5343549746a429a71abbb"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"fokpkk1Q8k3M/ZmQHdxXNY3duwA1Gfh4432zbI84pF48WO3asJKEjNy50fS+ZNyz028lyYTnpgbhGlStveEIBw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-07T18:36:36.428615Z","bundle_sha256":"8a4ae218e82942589010aa947e1a602013f2a1e5026c5915da76cc090e2cf452"}}